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<table width="100%" summary="page for metals"><tr><td>metals</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>
Data from heavy metal mixture experiments
</h2>

<h3>Description</h3>

<p>Data are from a study of the response of the cyanobacterial self-luminescent metallothionein-based whole-cell biosensor Synechoccocus elongatus PCC 7942 pBG2120 to binary mixtures of 6 heavy metals (Zn, Cu, Cd, Ag, Co and Hg).
</p>


<h3>Usage</h3>

<pre>data("metals")</pre>


<h3>Format</h3>

<p>A data frame with 543 observations on the following 3 variables.
</p>

<dl>
<dt><code>metal</code></dt><dd><p>a factor with levels <code>Ag</code> <code>AgCd</code> <code>Cd</code> <code>Co</code> <code>CoAg</code> <code>CoCd</code> <code>Cu</code> <code>CuAg</code> <code>CuCd</code> <code>CuCo</code> <code>CuHg</code> <code>CuZn</code> <code>Hg</code> <code>HgCd</code> <code>HgCo</code> <code>Zn</code> <code>ZnAg</code> <code>ZnCd</code> <code>ZnCo</code> <code>ZnHg</code></p>
</dd>
<dt><code>conc</code></dt><dd><p>a numeric vector of concentrations</p>
</dd>
<dt><code>BIF</code></dt><dd><p>a numeric vector of luminescence induction factors</p>
</dd>
</dl>



<h3>Details</h3>

<p>Data are from the study described by Martin-Betancor et al. (2015).
</p>


<h3>Source</h3>

<p>Martin-Betancor, K. and Ritz, C. and Fernandez-Pinas, F. and Leganes, F. and Rodea-Palomares, I. (2015) 
Defining an additivity framework for mixture research in inducible whole-cell biosensors,
<em>Scientific Reports</em>
<b>17200</b>.</p>


<h3>Examples</h3>

<pre>
## One example from the paper by Martin-Betancor et al (2015)

## Figure 2

## Fitting a model for "Zn"
Zn.lgau &lt;- drm(BIF ~ conc, data = subset(metals, metal == "Zn"), 
fct = lgaussian(), bcVal = 0, bcAdd = 10)

## Plotting data and fitted curve
plot(Zn.lgau, log = "", type = "all", 
xlab = expression(paste(plain("Zn")^plain("2+"), " ", mu, "", plain("M"))))

## Calculating effective doses
ED(Zn.lgau, 50, interval = "delta")
ED(Zn.lgau, -50, interval = "delta", bound = FALSE)
ED(Zn.lgau, 99.999,interval = "delta")  # approx. for ED0

## Fitting a model for "Cu"
Cu.lgau &lt;- drm(BIF ~ conc, data = subset(metals, metal == "Cu"), 
fct = lgaussian()) 

## Fitting a model for the mixture Cu-Zn
CuZn.lgau &lt;- drm(BIF ~ conc, data = subset(metals, metal == "CuZn"), 
fct = lgaussian()) 

## Calculating effects needed for the FA-CI plot
CuZn.effects &lt;- CIcompX(0.015, list(CuZn.lgau, Cu.lgau, Zn.lgau), 
c(-5, -10, -20, -30, -40, -50, -60, -70, -80, -90, -99, 99, 90, 80, 70, 60, 50, 40, 30, 20, 10))

## Reproducing the FA-cI plot shown in Figure 5d
plotFACI(CuZn.effects, "ED", ylim = c(0.8, 1.6), showPoints = TRUE)

</pre>


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